3  Results

library(ggplot2)
library(dplyr)
library(tidyr)
library(naniar)
library(ggmap)
library(lubridate)
library(sf)
library(dygraphs)
library(xts)
library(ggiraph)
library(sf)

data <- read.csv("NYPD_Arrest_Data.csv", na.strings = c("(null)", "N/A"))

### Data Preprocessing step
data <- na.omit(data)
data$ARREST_DATE <- as.Date(data$ARREST_DATE, format = "%m/%d/%Y")
data <- data |>
  mutate(ARREST_BORO = case_when(
    ARREST_BORO == "B" ~ "Bronx",
    ARREST_BORO == "S" ~ "Staten Island",
    ARREST_BORO == "K" ~ "Brooklyn",
    ARREST_BORO == "M" ~ "Manhattan",
    ARREST_BORO == "Q" ~ "Queens"
  )) 

daily_data <- data |>
  group_by(ARREST_DATE) |>
  summarise(Count = n(), .groups = "drop")


ggplot(daily_data, aes(x = ARREST_DATE, y = Count)) +
  geom_line(size = 0.8, alpha = 0.8) +
  labs(
    title = "Daily NYPD Arrests",
    subtitle = "From January 1st to September 30th",
    x = "Date",
    y = "Number of Arrests",
    color = "Borough"
  ) +
  scale_x_date(date_breaks = "2 week", date_labels = "%b %d") +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    plot.subtitle = element_text(size = 12),
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.title = element_text(size = 12),
    legend.text = element_text(size = 10)
  )

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

data <- data |>
  mutate(Weekday = wday(ARREST_DATE, label = TRUE, abbr = TRUE))  

weekday_summary <- data |>
  group_by(ARREST_DATE, Weekday) |>
  summarise(Count = n(), .groups = "drop")  

ggplot(weekday_summary, aes(x = ARREST_DATE, y = Count, group = Weekday, fill = Count)) +
  geom_area(alpha = 0.8) +  
  geom_line(size = 1, color = "black") +  
  facet_grid(Weekday ~ ., scales = "fixed", switch = "y") +  
  scale_fill_gradient(
    low = "lightblue",  
    high = "darkblue",  
    name = "Arrest Count"  
  ) +
  scale_x_date(date_breaks = "1 month", date_labels = "%b") +
  labs(
    title = "Daily NYPD Arrests by Weekday",
    x = "Date",
    y = "Number of Arrests"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    axis.text.x = element_text(angle = 45, hjust = 1), 
    strip.text.y.left = element_text(angle = 0),      
    strip.placement = "outside",                     
    legend.position = "right"                    
  )

daily_summary_by_borough <- data |>
  group_by(ARREST_DATE, ARREST_BORO) |>
  summarise(Count = n(), .groups = "drop")

wide_data <- tidyr::pivot_wider(daily_summary_by_borough, 
                                names_from = ARREST_BORO, 
                                values_from = Count, 
                                values_fill = 0)

wide_data$ARREST_DATE <- as.Date(wide_data$ARREST_DATE)

time_series_obj <- xts(wide_data[,-1], order.by = wide_data$ARREST_DATE)

custom_colors <- c(
  "Bronx" = "#E7298A",    
  "Brooklyn" = "#6495ED", 
  "Manhattan" = "#E6AB02",
  "Queens" = "#66A61E",   
  "Staten Island" = "#7570B3" 
)

dygraph(time_series_obj, main = "Daily NYPD Arrests") |>
  dyAxis("y", label = "Number of Arrests", valueRange = c(0, 400)) |>
  dyAxis("x", label = "Date") |>
  dyRangeSelector() |>
  dyLegend(width = 300, labelsSeparateLines = TRUE) |>
  dyOptions(colors = unname(custom_colors), strokeWidth = 2, gridLineColor = "#DDDDDD") 

daily_summary_by_borough <- data |>
  group_by(ARREST_DATE, ARREST_BORO) |>
  summarise(Count = n(), .groups = "drop")

ggplot(daily_summary_by_borough, aes(x = ARREST_DATE, y = Count, color = ARREST_BORO)) +
  geom_line(size = 0.8, alpha = 0.8) +
  labs(
    title = "Daily NYPD Arrests",
    subtitle = "From January 1st to September 30th",
    x = "Date",
    y = "Number of Arrests",
    color = "Borough"
  ) +
  scale_x_date(date_breaks = "2 week", date_labels = "%b %d") +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    plot.subtitle = element_text(size = 12),
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.title = element_text(size = 12),
    legend.text = element_text(size = 10)
  )

weekly_summary_by_borough <- data |>
  mutate(Week = floor_date(ARREST_DATE, unit = "week")) |>  # Create a 'Week' column
  group_by(Week, ARREST_BORO) |>                           # Group by week and borough
  summarise(Count = n(), .groups = "drop") 
max_week <- max(weekly_summary_by_borough$Week)
weekly_summary_filtered <- weekly_summary_by_borough |>
  filter(Week < max_week)

ggplot(weekly_summary_filtered, aes(x = Week, y = Count, color = ARREST_BORO)) +
  geom_line(size = 1, alpha = 0.8) +
  scale_x_date(date_breaks = "2 week", date_labels = "%b %d") + # Weekly x-axis labels
  labs(
    title = "Weekly NYPD Arrests",
    subtitle = "From January 1st to September 30th",
    x = "Week",
    y = "Number of Arrests",
    color = "Borough"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    plot.subtitle = element_text(size = 12),
    axis.text.x = element_text(angle = 45, hjust = 1), # Rotate x-axis labels
    axis.title.x = element_text(size = 14),
    legend.title = element_text(size = 12),
    legend.text = element_text(size = 10)
  )

nyc_sf <- read_sf("new-york-city-boroughs.geojson")
data <- data |>
  filter(Longitude != 0 & Latitude != 0)
arrest_sf <- st_as_sf(data, coords = c("Longitude", "Latitude"), crs = 4326)

borough_arrest_count <- arrest_sf |>
  st_drop_geometry() |>
  group_by(ARREST_BORO) |>
  summarise(total_arrests = n())

nyc_sf <- nyc_sf |>
  left_join(borough_arrest_count, by = c("name" = "ARREST_BORO")) |>
  mutate(tooltip = paste(name, "<br>Total Arrests:", total_arrests))

interactive_map <- ggplot() +
  geom_sf_interactive(
    data = nyc_sf,
    aes(fill = name, geometry = geometry, tooltip = tooltip),
    color = "black",
    size = 0.3,
    alpha = 0.5
  ) +
  geom_sf(
    data = arrest_sf,
    aes(geometry = geometry),
    color = "red",
    size = 0.05,
    alpha = 0.4,
    stroke = 0.3,
    shape = 1
  ) +
  labs(
    title = "Arrest Locations in NYC",
    x = "Longitude",
    y = "Latitude",
    fill = "Borough"
  ) +
  coord_sf() +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    plot.subtitle = element_text(size = 12, face = "italic"),
    legend.title = element_text(size = 12),
    legend.text = element_text(size = 10),
    plot.margin = margin(1, 1, 1, 1, "cm")
  )

girafe(ggobj = interactive_map)